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Payoff‐dependent adoption of strategies is one of the most common assumptions in evolutionary game theory. If individuals are able to observe both the strategies and the payoffs of their neighbors, they tend to switch to the most successful strategy. This, however, often results in a dilemma situation if payoffs depend on the strategies chosen by the counterparts. If everyone tries to maximize the personal payoff, individuals may end up with obtaining less than expected. Evolutionary game theory has suggested different routes out of this dilemma situation. We propose a rarely explored solution, namely to provide individuals with less information, instead of more information. In the absence of full information about neighbors' strategies and resulting payoffs, individuals tend to simply follow the action of the majority, without calculating all consequences. This kind of social herding leads to a strong amplification of locally dominating strategies. At the same time, the tension between the most successful and the most frequently used strategy may increase. Using an agent‐based model that combines elements of strategic decisions and social herding, we explore the conditions under which less information may help to avoid social dilemma. We also design ICT‐based interaction mechanisms for individuals, to enhance cooperation.